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All Journal Efisiensi : Kajian Ilmu Administrasi Jurnal Ilmu Komputer Jurnal Ilmiah Kursor Telematika SMATIKA Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer JURNAL ILMIAH INFORMATIKA JCES (Journal of Character Education Society) SINTECH (Science and Information Technology) Journal Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal Tekno Insentif IJISTECH (International Journal Of Information System & Technology) The IJICS (International Journal of Informatics and Computer Science) JUTEKIN (Jurnal Manajemen Informatika) JUMANJI (Jurnal Masyarakat Informatika Unjani) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Manajemen Informatika Jurnal Sistem Cerdas Jurnal Tekno Kompak MULTINETICS Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Dinasti International Journal of Education Management and Social Science Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika JATI (Jurnal Mahasiswa Teknik Informatika) Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS Journal of Computer System and Informatics (JoSYC) JIKA (Jurnal Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Journal of Research in Instructional Merpati JUSTIN (Jurnal Sistem dan Teknologi Informasi) JOMLAI: Journal of Machine Learning and Artificial Intelligence Competitive Jurnal Informatika: Jurnal Pengembangan IT Jurnal Ilmiah Sistem Informasi The Indonesian Journal of Computer Science

Prianto, Cahyo

Universitas Logistik Dan Bisnis Internasional

Author-ID : 5510005

Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Transportation Other

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Pengembangan Sistem Transportasi Pada Gudang In-Transit Merge Dengan Integrasi Sistem Android Cahyo Prianto; Harun Ar-Rasyid; Nico Ekklesia Sembiring
Komputika : Jurnal Sistem Komputer Vol 9 No 2 (2020): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v9i2.3005

The problem that arises in the business activities of companies that are based on the sale of goods is the lack of a system that can help companies carry out the activities of shipping goods from warehouses to stores. Therefore, in this project, a web-based and Android-integrated transportation and routing selection system will be developed. So that it can facilitate officers in choosing the type of transportation and also the driver in seeing the route.The function of selecting the type of transportation is very important to assist officers in selecting the type of transportation suitable for delivering goods. As well as with the routing function that can help the driver to find out the intended route. By developing this system, companies can easily access and monitor goods sent to the store and guarantee the safety of the goods sent will get to the store through the token feature. This application is designed using the PHP programming language and Code Igniter (CI) and MySQL framework as the database and UML as the analysis process and also integrates the Android system. This application can be accessed by super administrators, warehouse officers, staff, drivers, and shop owners who have registered in this application, which makes this application convenient for users to use. Keywords - Development; System; Warehouse; In-Transit Merge; Transportation.

Segmentasi Pelanggan Produk Digital Service Indihome Menggunakan Algoritma K-Means Berbasis Python Nisa Hanum Harani; Cahyo Prianto; Fikri Aldi Nugraha
Jurnal Manajemen Informatika (JAMIKA) Vol 10 No 2 (2020): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v10i2.2683

Telekomunikasi Indonesia is one of the companies that prioritize customers, but there is no information about customer characteristics. In this research, an analysis of customer characteristics used as a basis for determining customer segmentation and customer profiling for digital products add on Indihome services using the K-Means Algorithm. Determination of the best number of clusters done using the Elbow method and a value of K = 3 obtained, so that customer data grouped into three segments. Customer data processing is divided into 3 simulations with the percentage of train data and test data 80% - 20%, 70% - 30% and 50% - 50%. The data used totaled 1392 records as a population where the data will used to find the characteristics of each data. Cluster evaluations carried out using the Silhouette Index, Davies Bouldin Index, and Calinski Harabasz Index methods. The results of the study show that the third simulation is the best based on cluster evaluation with 50% data train presentation and 50% data test where customer profiling is seen by analyzing the members of each cluster from the third simulation where cluster 0 has 396 customer members with a customer category that provides the biggest profit for the company, cluster 1 has members of 286 customers in the category of customers who unwittingly have great potential in providing benefits for the company, and cluster 2 has a member of 14 customers in the customer category that provides fewer benefits than the cost of providing services.

Pemetaan Pelanggan IndiHome Sebagai Daerah Sasaran Promosi (Studi Kasus : Witel Bandung) Nisa Hanum Harani; Cahyo Prianto; Andri Fajar Sunandhar
Jurnal Manajemen Informatika (JAMIKA) Vol 10 No 2 (2020): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v10i2.2738

In this globalization era, marketing communication is very important to help increase sales promotion of indihome digital service products by utilizing customer location points that use indihome services. Currently there are many information systems that are used to support and solve problems in determining the location of a place. Determination of location can be done using mapping. The mapping of Indihome customers is done by utilizing a map provided by Google, the Google Maps API based on the address of the Indihome service customer. Therefore, we need a system to find out which areas use the most indihome services, so that it will make it easier to target promotions for indihome customers who have not used to add services to Indihome such as Movin, Indihome Gamers, Indihome Music, Indihome Music, Indihome Studies, Indihome Storage, Indihome Servers, Video Calls, and other additional packages. The results of this mapping can determine areas / regions that have the potential to be promoted in connection with the addition of indihome service products, so that it will have an impact on increasing customers and sales revenue of Add On products.

The Covid-19 Chatbot Application Using A Natural Language Processing Approach Cahyo Prianto; Nisa Hanum Harani
IJISTECH (International Journal of Information System and Technology) Vol 5, No 2 (2021): August
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i2.133

Cases exposed to the Covid-19 virus in Indonesia until June 2021 continue to experience a spike in increases, to handle it, various government policies continue to be rolled out and the public needs to be given correct, precise and fast information so that mutual awareness can be built to suppress cases exposed to COVID-19. With this background, this study aims to design and build a COVID-19 chatbot system based on artificial intelligence based on the Natural Language Processing algorithm. This chatbot is expected to be a place to ask questions about all things related to covid-19 so that it can become a personal assistant with two-way communication that can be accessed quickly for 24 hours. This chatbot system was built using the Python programming language, Node.js server and MariaDB as the database. As a client, this chatbot is integrated with the popular instant messaging application in Indonesia, namely WhatsApp. The data set used to train the chatbot was 369 question data and spread into 46 question tags. Testing the chatbot system using blackbox testing, and to test the expected output, the chatbot was tested using 350 testing data and the accuracy rate of the chatbot in answering reached 54%.

Rancang Bangun Aplikasi Penentuan Kelayakan Pemberian Pinjaman Kepada Pensiun Menggunakan Metode Weighted Product Kezia Tirza Naramessakh; Cahyo Prianto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1289

In supporting the operation of PT. Pos Indonesia, one of which is offering retirees such as pension savings and pension credit. Credit is the provision of money or bills based on an agreement or loan agreement between a company and another party. In providing pension credit, it must be accurate and accurate for retirees who are entitled or eligible to get a loan. So the author makes an application to determine the feasibility of lending in order to make it easier to determine which retirees are eligible to be given a credit loan. This study uses the Weighted Product (WP) method, which is one method of decision making. By using the Weighted Product method can help in making lending decisions by doing a ranking process that will determine the best alternative from retirees. The author uses five criteria, namely, the amount of salary, loan amount, age, credit period, and what credit. The application of determining the feasibility of lending to pensions is based on a website using the code igniter framework. For designing or modeling this application uses UML (Unified Modeling Language). This research resulted in an application that helped in determining a proper pension to be given a pension loan using Weighted Product.

Analisis Sentimen Terhadap Kandidat Presiden Republik Indonesia Pada Pemilu 2019 di Media Sosial Twitter Cahyo Prianto; Nisa Hanum Harani; Indra Firmansyah
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1549

The development of technology today has been growing rapidly and has an impact on the behavior patterns of people who feel it. The Ministry of Communication and Information (KOMINFO) released a data that of 265 million people of Indonesia, there are around 54% have used internet technology or about 143 million people. In one survey IDN Research Institute said that there are three Social Media that are widely used in Indonesia, namely Facebook, Instagram and Twitter. This study focuses on extracting data in the form of text produced from social media twitter that responds to the account of the RI presidential candidates in the 2019 elections. Sentiment analysis is obtained through tweet classification using sentiment analysis tools such as NRC Lexicon and Bing Lexicon so that information is obtained in the form of positive polarity and negative polarity from community tweets towards the Presidential candidates in the 2019 elections. Using March data before the 2019 election, for candidate 01 Joko Widodo, the NRC Lexicon analysis gave a value of 249 and bing lexicon of 267 with an average value of 0.11, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 195 and bing lexicon of 204 with an average value of 0.085. Using april data after the 2019 election. Candidate 01 Joko Widodo still received a lot of responses from netizens but the sentiment value shifted more negatively compared to candidate 02 Prabowo Subianto. For candidate 01 Joko Widodo the NRC Lexicon analysis gave a value of 17 and bing lexicon of -273 with an average value of -0,246, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 238 and bing lexicon of -73 with an average value of -0.02430939.

Analisis Sentimen UU Omnibus Law pada Twitter Menggunakan Metode Support Vector Machine Syafrial Fachri Pane; Alfadian Owen; Cahyo Prianto
InComTech : Jurnal Telekomunikasi dan Komputer Vol 11, No 2 (2021)
Publisher : Department of Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/incomtech.v11i2.10874

Pada media sosial Twitter semua orang bebas memberikan opini ataupun memberikan tweet yang bermanfaat bagi pengguna media sosial tersebut. Namun dalam memberikan opini masyarakat harus bisa membedakan opini yang positif, negatif, ataupun netral. Permasalahan yang ada adalah belum adanya pemberian sentimen otomatis dalam tema tertentu. Maka dari itu dibuatlah sistem untuk memberikan sentimen secara otomatis agar masyarakat tahu opini yang positif, negatif, dan netral. Dalam analisis sentimen ini dilakukan dengan memanfaatkan machine learning salah satu metodenya adalah Support Vector Machine yang merupakan metode pengklasifikasian supervised learning yang dapat membedakan opini positif, negatif, dan netral dalam penelitian ini, menggunakan Bahasa pemrograman Python, dan menggunakan data yang berasal dari Twitter sebanyak 150. Data tersebut diambil pada tanggal 3 November 2020 sampai 9 November 2020 setelah Omnibus Law disahkan. Penerapan metode Support Vector Machine memiliki tiga tahap yaitu mengambil data opini masyarakat Indonesia tentang UU Omnibus Law dengan melakukan Scraping, lalu dilanjutkan ke tahap Text Preprocessing, dan Feature Extraction. Menghasilkan akurasi sebesar 83% dengan menggunakan teknik K-Fold Cross-Validation sehingga hasil yang didapatkan cukup akurat.

Sentiment Analysis of Covid-19 As A Social Media Pandemic Cahyo Prianto; Nisa Hanum Harani
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

A large amount of information about Covid-19 that spreads quickly can lead to a perception of opinion and sentiment for those who read it. This research studies how text networking is formed, sentiment analysis and topics modelling that is widely discussed related to the Covid-19 theme. The text networking analysis was carried out on data taken from 4 different times, namely on 26 March, 29 March, 28 June and 23 July 2020 giving the result that the largest edge, nodes and modularity were in the conversation data on July 23, 2020. Sentiment analysis shows how the public responds to the Covid-19 pandemic. Sentiment analysis from tweet data in March 2020 showed 51% as positive sentiment and 49% as negative sentiment, with an accuracy rate of 0.7586, specificity 0.6667, prevalence 0.5862. Then tweet data in June 2020 showed 59% as negative sentiment and 41% as positive sentiment, with an accuracy rate of 0.6486, specificity 0.6111, prevalence 0.5135. Analysis of topic modelling has succeeded in collecting words related to certain topics, such as the data on March 26, 2020, representing talks related to the topic of "doing activities from home", "health", and "government policy". The data on March 29, 2020, represent talks related to the topic of "activities from home", "expression of feelings", "new habits". The data on June 28, 2020, represent talks related to the topic of "health protocol", "social assistance", "health". And on July 23, 2020 data represents talks related to the topic of "data security", "fine policy", and "policy".

Implementation of K-Means Methods In Clustering Students Ability Levels in English Language Cahyo Prianto; Rd Nuraini; Andi Tenri Wali
The IJICS (International Journal of Informatics and Computer Science) Vol 3, No 2 (2019): September 2019
Publisher : STMIK Budi Darma

Nowadays, English extremely needs to be controlled, especially students, in communicating and reading also understanding literature written in English. In achieving mastery of English, the students, in this case, the students who are not majoring in English are given a common base subject of English. In Politeknik Indonesia, especially majoring in a Bachelor's Degree in Informatics Engineering, teaching English is using the direct method, to find out the results of teaching English within three semesters. Therefore, by doing this research for classifying the level of ability of students into three categories, they are Beginner, intermediate and advanced. The objective of the grouping is to determine how many students who have the capability level is low, medium and high so that the faculty can determine the average level of students' proficiency and the lecturers can intervene to conduct teaching in developing the students' knowledge of English. The classification used the K-Means clustering algorithm, which is one algorithm that classifies the same data on specific groups and different data in the other group. The results of this study by applying the k-means clustering method is the researchers can classify the students based on students' ability levels either they are beginner, intermediate or advanced.

Co-Authors Adiningrum, Nur Tri Ramadhanti Adiningrum, Nur Tri Ramadhanti Alfadian Owen Amalia, Fahriza Rizky Aminuyati Andarsyah, Roni Andi Tenri Wali Andri Fajar Sunandhar Arjun Yuda Firwanda Azzahra, Fedhira Syaila Putri Burhanudin Zuhri Dellavianti Nishfi Ilmiah Huda Dian Markuci Fahira Fahira Fedhira Fikri Aldi Nugraha Firwanda, Arjun Yuda Habib Abdul Rasyid Hanna Theresia Siregar Hanum, Nisa Harani, Nisa Hanum Harun Ar-Rasyid Helmi Azhar Hutabarat, Rizkyria Angelina Pandapotan Ilyas Tri Khaqiqi, M Indra Firmansyah Kamaluddin, Rendy Kezia Tirza Naramessakh Kezia Tirza Naramessakh Kishendrian, Hanan M Ilyas Tri Khaqiqi Mariana Rospilinda Siki Markuci, Dian Mohamad Nurkamal Fauzan Mubassiran Mubassiran, Mubassiran Muh Kusnadi Muhammad Ibnu Choldun Muhammad Nazhim Maulana Muhammad Rifqi Daffa Ulhaq Muhammad Yusril Helmi Setyawan Muhammad Yusuf, Hadi Nawaf Naofal Nico Ekklesia Sembiring Nisa Hanum Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nurkamal Fauzan, Mohamad Nurul Izza Hamka Nurul Izza Hamka Nurul Lutfiasih Oktaviami Manullang Oktaviami Manullang Pertiwi, Aryka Anisa Rahayu, Woro Isti Rd Nuraini Rd.Nuraeni Siti Fatonah Riza, Noviana Rolly Maulana Awangga Rolly Maulana Awangga, Rolly Maulana Roni Andarsyah Roni Andarsyah Roni Andarsyah Roni Andarsyah Rukmi Juwita Setiadi, Hilman Setyawan, Muhammad Yusril Helmi Shinta Amelia Shinta Amelia Sulaksono, Al Novianti Ramadhani Supriady, Supriady Syafrial Fachri Pane Syafrial Fachri Pane Syafrial Fachri Pane, Syafrial Fachri Syahra, anita alfi Vegita, Yola Zian Asti Dwiyanti Zuhri, Burhanudin

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